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ErrorLens – AI-Powered Debugging Assistant

ErrorLens is a developer-focused debugging tool that analyzes runtime errors and code snippets to identify root causes and suggest multiple resolution paths with confidence scoring.

🚨 Problem

Debugging is one of the most time-consuming parts of development. Developers often waste time:

  • Interpreting vague error messages
  • Tracing issues across unfamiliar code
  • Searching through forums for possible fixes

💡 Solution

ErrorLens reduces debugging time by providing structured, context-aware analysis of errors.

Developers can input an error message and related code, and the system will:

  • Explain the error in simple terms
  • Identify the root cause
  • Suggest multiple possible fixes
  • Provide a confidence score for each analysis

⚙️ How It Works

  1. User submits an error and code snippet
  2. Backend processes and enhances the input with pattern detection
  3. AI model analyzes the context using structured prompting
  4. Response is parsed into a consistent JSON format
  5. Frontend displays results in a clean, developer-friendly UI

🧠 Key Features

  • Structured error analysis (not raw AI output)
  • Root cause identification
  • Multiple fix suggestions
  • Confidence scoring system
  • Developer-focused UI with code editor support

🛠️ Tech Stack

Frontend:

  • React + TypeScript
  • Tailwind CSS
  • Monaco Editor

Backend:

  • Node.js + Express + TypeScript

AI Integration:

  • OpenAI / Claude API with structured prompting

🧱 Architecture

Frontend (React) ↓ Backend API (Node.js) ↓ AI Processing Layer

🎯 Design Focus

This project focuses on:

  • Practical developer utility
  • Clean and structured output
  • Minimal but effective UI
  • Real-world debugging workflows

🚀 Future Improvements

  • Stack-specific error detection (React, Node, MongoDB)
  • Error history tracking
  • Authentication and saved sessions
  • Enhanced confidence scoring using heuristics

📌 Why This Project

Instead of building a generic AI wrapper, ErrorLens focuses on a real developer pain point—debugging—and delivers a structured, actionable solution.


This project demonstrates:

  • API design and backend structuring
  • Prompt engineering and response shaping
  • Frontend state management and UI composition
  • Problem-solving with AI integration

🔗 Live Demo

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📷 Preview

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AI-powered debugging assistant that analyzes code errors, identifies root causes, and suggests fixes with confidence scoring.

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